3D-based skin roughness measurement for lesion classification
Skin surface roughness can be changed due to skin lesion progression. The evaluation of the damage of the skin is assessed on the base of clinical experience of dermatologists. Currently, the assessment of skin surface is made by running a finger across the skin. It is found that this tactile evalua...
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creator | Hani, A.F.M. Nugroho, H. Prakasa, E. Fitriyah, H. Affandi, A.M. Hussein, S.H. |
description | Skin surface roughness can be changed due to skin lesion progression. The evaluation of the damage of the skin is assessed on the base of clinical experience of dermatologists. Currently, the assessment of skin surface is made by running a finger across the skin. It is found that this tactile evaluation may result in inter and intra variations. The objective of our research is to develop an objective assessment tool in evaluation skin roughness. Psoriasis is used as a sample of skin lesion that can change skin surface roughness as its extents develop. 3D surface images of 120 psoriasis lesions scanned from 29 patients are analysed in the study. The lesions are previously grouped into four categorises based on its tactile characteristics by dermatologists. The proposed method converts the 3D images into 2D height maps. The 2D height maps are then fitted and filtered using averaging filter. Finally, Mean Square Error (MSE) between the fitted and filtered 2D height maps are computed and utilized as skin roughness descriptors. Results show that the proposed method has been able to differentiate each lesion according to its group perfectly. |
doi_str_mv | 10.1109/ISIEA.2009.5356494 |
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The evaluation of the damage of the skin is assessed on the base of clinical experience of dermatologists. Currently, the assessment of skin surface is made by running a finger across the skin. It is found that this tactile evaluation may result in inter and intra variations. The objective of our research is to develop an objective assessment tool in evaluation skin roughness. Psoriasis is used as a sample of skin lesion that can change skin surface roughness as its extents develop. 3D surface images of 120 psoriasis lesions scanned from 29 patients are analysed in the study. The lesions are previously grouped into four categorises based on its tactile characteristics by dermatologists. The proposed method converts the 3D images into 2D height maps. The 2D height maps are then fitted and filtered using averaging filter. Finally, Mean Square Error (MSE) between the fitted and filtered 2D height maps are computed and utilized as skin roughness descriptors. 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The evaluation of the damage of the skin is assessed on the base of clinical experience of dermatologists. Currently, the assessment of skin surface is made by running a finger across the skin. It is found that this tactile evaluation may result in inter and intra variations. The objective of our research is to develop an objective assessment tool in evaluation skin roughness. Psoriasis is used as a sample of skin lesion that can change skin surface roughness as its extents develop. 3D surface images of 120 psoriasis lesions scanned from 29 patients are analysed in the study. The lesions are previously grouped into four categorises based on its tactile characteristics by dermatologists. The proposed method converts the 3D images into 2D height maps. The 2D height maps are then fitted and filtered using averaging filter. Finally, Mean Square Error (MSE) between the fitted and filtered 2D height maps are computed and utilized as skin roughness descriptors. Results show that the proposed method has been able to differentiate each lesion according to its group perfectly.</description><subject>Diseases</subject><subject>Industrial electronics</subject><subject>Lesions</subject><subject>Magnetic resonance imaging</subject><subject>Optical imaging</subject><subject>Optical surface waves</subject><subject>Rough surfaces</subject><subject>Skin</subject><subject>Surface roughness</subject><subject>Ultrasonic imaging</subject><isbn>9781424446810</isbn><isbn>1424446813</isbn><isbn>9781424446834</isbn><isbn>142444683X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkMtOwzAURI1QJaDkB2DjH0i4jq9fCxZVKRCpEgu6r25SGwx5oDhd8PcE0Q2zGR1pNBoNYzcCCiHA3VWv1WZVlACuUFJpdHjGMmeswBIRtZV4_o8FLNjVb9wBGqsvWJbSB8xCVTqrL9m9fMhrSv7A02fs-Tgc3957nxLvPKXj6DvfTzwMI299ikPPm5ZSiiE2NM14zRaB2uSzky_Z7nGzWz_n25enar3a5tHBlCuHRkkLpA9hHiWlE4FMjSVJKWonqLGNsU1AoYSwQZfKBUkARiugWhq5ZLd_tdF7v_8aY0fj9_50gPwBocpLQQ</recordid><startdate>200910</startdate><enddate>200910</enddate><creator>Hani, A.F.M.</creator><creator>Nugroho, H.</creator><creator>Prakasa, E.</creator><creator>Fitriyah, H.</creator><creator>Affandi, A.M.</creator><creator>Hussein, S.H.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200910</creationdate><title>3D-based skin roughness measurement for lesion classification</title><author>Hani, A.F.M. ; Nugroho, H. ; Prakasa, E. ; Fitriyah, H. ; Affandi, A.M. ; Hussein, S.H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-59475380a6df4463391fa7b42a331b91ac8c78cf415118f6259f3a007650ab373</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Diseases</topic><topic>Industrial electronics</topic><topic>Lesions</topic><topic>Magnetic resonance imaging</topic><topic>Optical imaging</topic><topic>Optical surface waves</topic><topic>Rough surfaces</topic><topic>Skin</topic><topic>Surface roughness</topic><topic>Ultrasonic imaging</topic><toplevel>online_resources</toplevel><creatorcontrib>Hani, A.F.M.</creatorcontrib><creatorcontrib>Nugroho, H.</creatorcontrib><creatorcontrib>Prakasa, E.</creatorcontrib><creatorcontrib>Fitriyah, H.</creatorcontrib><creatorcontrib>Affandi, A.M.</creatorcontrib><creatorcontrib>Hussein, S.H.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hani, A.F.M.</au><au>Nugroho, H.</au><au>Prakasa, E.</au><au>Fitriyah, H.</au><au>Affandi, A.M.</au><au>Hussein, S.H.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>3D-based skin roughness measurement for lesion classification</atitle><btitle>2009 IEEE Symposium on Industrial Electronics & Applications</btitle><stitle>ISIEA</stitle><date>2009-10</date><risdate>2009</risdate><volume>1</volume><spage>15</spage><epage>19</epage><pages>15-19</pages><isbn>9781424446810</isbn><isbn>1424446813</isbn><eisbn>9781424446834</eisbn><eisbn>142444683X</eisbn><abstract>Skin surface roughness can be changed due to skin lesion progression. The evaluation of the damage of the skin is assessed on the base of clinical experience of dermatologists. Currently, the assessment of skin surface is made by running a finger across the skin. It is found that this tactile evaluation may result in inter and intra variations. The objective of our research is to develop an objective assessment tool in evaluation skin roughness. Psoriasis is used as a sample of skin lesion that can change skin surface roughness as its extents develop. 3D surface images of 120 psoriasis lesions scanned from 29 patients are analysed in the study. The lesions are previously grouped into four categorises based on its tactile characteristics by dermatologists. The proposed method converts the 3D images into 2D height maps. The 2D height maps are then fitted and filtered using averaging filter. Finally, Mean Square Error (MSE) between the fitted and filtered 2D height maps are computed and utilized as skin roughness descriptors. Results show that the proposed method has been able to differentiate each lesion according to its group perfectly.</abstract><pub>IEEE</pub><doi>10.1109/ISIEA.2009.5356494</doi><tpages>5</tpages></addata></record> |
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subjects | Diseases Industrial electronics Lesions Magnetic resonance imaging Optical imaging Optical surface waves Rough surfaces Skin Surface roughness Ultrasonic imaging |
title | 3D-based skin roughness measurement for lesion classification |
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